In this paper, we propose a framework for energy-efficient (EE) design in reconfigurable intelligent surface (RIS)-assisted multi-satellite Internet of Things (IoT) networks, taking into account the imperfect channel state information (CSI). In this framework, the multi-satellite network is used to enhance communication capabilities, while the RIS is deployed to further improve EE performance. Our objective is to maximize the EE of the proposed network by jointly optimizing the active beamforming and scheduling of the satellites and the phase shifts of RIS under the transmit power constraint for each satellite, the elevation angle constraints, and the phase shift constraints of the RIS. To handle this non-convex and NP-hard optimization problem, we propose two efficient algorithms, i.e., the Dinkelbach-BigM-Successive-Penalty (DBSP) algorithm and the Lagrangian Dual Majorization (LDM) algorithm. The DBSP algorithm is based on the alternating optimization approach, which can effectively solve the formulated non-convex optimization problem with multiple dual and complex optimization variables. Specifically, we first employ the Dinkelbach method, successive convex approximation, big-M formulation, and semidefinite relaxation method to optimize the active beamforming and the scheduling of the satellites. In addition, the penalty convex-concave procedure approach is utilized to design the phase shifts of RIS. To reduce the complexity and improve computational efficiency, we propose the LDM algorithm and derive an analytical solution for active beamforming and phase shifts by exploiting the Lagrangian dual transform, quadratic transform, and majorization-minimization algorithms. Numerical simulations are conducted to demonstrate the efficiency and convergence behavior of the proposed algorithms. Moreover, it is also demonstrated that the proposed algorithms are superior to other benchmarks, corroborating the benefits of deploying an RIS in the multi-satellite network.

In recent years, line-of-sight multiple-input multiple-output (LoS-MIMO) systems have attracted significant attention for their potential in ultra-high throughput space communications. This work addresses E-band LEO satellite transmission with three advances: A dynamic spatio-temporal coupling model for non-orthogonal propagation and non-homologous clocks LoS-MIMO channels. A dual-feedback symbol timing recovery (STR) architecture integrating a frequency-domain timing offset detection (TOD) algorithm that combines an optimized Barton estimator and time-domain resampling, enabling continuous tracking and compensation for thousands of parts-per-million timing frequency deviations (TFDs). Closed-form expressions for TOD estimation error, loop convergence constraints, and residual timing jitter. Simulations under various transmitter delay differences and signal-to-noise ratios verify the resistance to TFD and low residual jitter of the algorithm, showing excellent agreement with theoretical predictions. To our knowledge, this is the first work to address STR architectures across multi-station with non-homologous clocks in satellite-to-ground LoS-MIMO systems, providing a foundational framework for future ultra-high-throughput space communications.

This paper studies jammer-assisted covert transmission with both transmitter and the jammer equipping with fluid antenna arrays. Performance analyses of reliability and covertness are conducted, based on which both transmitter’s and jammer’s transmit powers, beamforming vectors, and antennas’ positions are jointly designed to optimize covertness under the reliability constraint for two scenarios. In the first scenario, warden’s position is known. The global optimal solutions of the aforementioned variables are obtained, based on which the advantages of fluid antennas over fixed-position antennas are analytically revealed, and a series of Pareto optimal solutions for balancing reliability and covertness are demonstrated. In the second scenario, warden’s position is uncertain and is modeled by a general distribution function. The resultant intractable optimization problem is addressed by invoking the constrained stochastic successive convex approximation method. Numerical results show significant performance gains from fluid antennas.

This article investigates the simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) assisted secure transmissions in wireless powered communication (WPC) systems. According to the conditions of communication links, three scenarios are considered. Correspondingly, two transmission schemes are proposed for outdoor and indoor users to enhance the reliability and security of the communication system in each scenario. To be specific, for the scenario-I with blocked energy harvesting links, the scenario-I based information transmission of outdoor-user and cooperative jamming of indoor-user (IbTOJI) scheme, and cooperative jamming of outdoor-user and information transmission of indoor-user (IbJOTI) scheme are proposed, respectively. For the scenario-II with blocked information transmission (IT) links, scenario-II-based IT of outdoor-user and cooperative jamming of indoor-user (IIbTOJI) scheme, and cooperative jamming of outdoor-user and IT of indoor-user (IIbJOTI) scheme are proposed, respectively. For the scenario-III which deploys a hybrid access point (HAP), the direct links of the energy harvesting and IT are blocked. Scenario-III-based IT of outdoor-user and cooperative jamming of indoor-user (IIIbTOJI) scheme, and cooperative jamming of outdoor-user and IT of indoor-user (IIIbJOTI) scheme are proposed, respectively. We analyze the closed-form expressions of outage probability and intercept probability for each scheme. The result shows that IIIbTOJI scheme has the best reliable performance among the proposed schemes, and IbJOTI and IIIbJOTI schemes perform best in security.

The miniaturization of satellite payloads and the reduction in launch costs have driven the rapid development of low Earth orbit (LEO) satellites in the fields of communication, navigation, and remote sensing (CNS), reshaping the industry and global information infrastructure. However, there remain significant challenges and obstacles in the application of LEO satellites within these domains. This article aims to provide a comprehensive analysis of LEO satellites, with particular emphasis on the development and challenges of communication payloads, to promote further research and applications in these areas. First, this article examines the evolution of LEO systems and communication payload capabilities from different historical perspectives and user demands. It then explores the opportunities for LEO satellites in the context of global communication infrastructure, particularly in enhancing global connectivity, supporting intelligent transportation through high-precision positioning, navigation, and timing (PNT), and advancing environmental monitoring via passive radar (PR) in remote sensing applications. By systematically reviewing the literature on network architectures, medium access control, physical-layer technologies, constellation designs, interference management, the application of artificial intelligence, and cost control strategies, this study identifies the major challenges these technologies face in CNS applications. Additionally, this article discusses future research directions, including large-scale constellations, multifunctional platform integration, advances in intelligence and automation, network convergence and interoperability, interference mitigation, and sustainability. These areas are explored to provide pathways for further technological advancements.

We propose a cross-layer optimization algorithm to minimize the average Age of Information (AoI) and at the same time maximizing the communication sum rate in a dual-functional reconfigurable intelligent surface (DF-RIS)-assisted Internet of Things (IoT) network, where the DF-RIS performs simultaneous information reflection and jamming to defend against an eavesdropper (Eve). Specifically, the transmission scheduling and resource allocation are adaptively co-designed to achieve secure low-latency communication in a more practical and detailed channel environment. For the case with perfect channel state information (CSI) of Eve and IoT devices, the transmission scheduling is transformed as a Markov decision process and optimized to find the optimal packet size by deep$\boldsymbol {Q}$-network. The resource allocation algorithm is performed to optimize subcarrier channels, transmit power, the scheduling matrix of the DF-RIS, and discrete phase shifts of the DF-RIS based on the alternating optimization method. For the imperfect CSI leads to an infinite number of inequality constraints, a robust resource allocation algorithm based on the transformed${\mathcal{S}}$-procedure is proposed, which can guarantee the security and low-latency of messages transmission. Simulation results show that the proposed algorithm can reduce the average AoI by at least 15.5% and increase communication sum rate by 9.2% than the existing baseline algorithms.

Jamming is regarded as an effective and popular way to assist covert wireless communications. However, if the warden uses a directional beam for detection, the effects of jamming may be alleviated or even be eliminated. This paper studies the jammer-assisted covert communication schemes against directional beam. Two specific collaborative unmanned aerial vehicle (UAV) communication scenarios are considered. In scenario 1, the warden’s beam direction and beamwidth are unknown. In scenario 2, the warden’s beamwidth is known, but his location is unknown. For both scenarios, the jammer deployment strategies for confronting directional beam are proposed. Closed-form expressions are developed to evaluate the warden’s detection performance, based on which conclusions regarding the optimal deployment of the UAVs are proved. The UAVs’ locations and transmit power are jointly optimized to enhance reception while satisfying covert constraints. Furthermore, scenario 1 is extended to the case where the warden’s location is imperfectly known. Both theoretical and numerical results reveal that collaborative beamforming can provide covert performance gains via dispersing the power over the space domain, which is similar to the role of direct sequence spread spectrum in frequency domain.

Satellite Internet of Things (IoT) network plays a crucial role in providing global coverage. To improve the efficient utilization of spectral and hardware resources in the satellite communications, integrated sensing and communication (ISAC) has attracted considerable attention. In addition, the greater broadcast nature of the satellite-terrestrial integrated network makes it extremely vulnerable to illegal eavesdropper (Eve). In this paper, we adopt non-orthogonal multiple access (NOMA) to support more users for the ISAC of a low earth orbit satellite system, with well-designed precoding according to whether the channel state information (CSI) of the Eve is perfect to ensure security. First, a joint precoding optimization problem is proposed to maximize the sum secrecy rate (SSR) of multiple users by considering the perfect CSI of the Eve. Then, we formulate a secure precoding optimization problem based on the imperfect CSI of the Eve, aiming to maximize the SSR of multiple users via artificial jamming. To address the non-convexity of the optimization problems, we transform them into the convex ones based on successive convex approximation, which includes Taylor’s approximation, arithmetic-geometric mean inequality, and linear matrix inequality. In addition, semi-definite relaxation and iterative penalty function methods are respectively used to optimize the secure precoding problems in the two cases: perfect CSI and imperfect CSI. Simulation results show that the proposed NOMA-ISAC scheme improves the SSR compared to the traditional time division multiple access while ensuring the sensing performance.

In this paper, we investigate the physical layer security for multi-beam satellite communications in the presence of multiple eavesdroppers (Eves). In particular, a worst-case eavesdropping scheme is considered. To achieve a positive secrecy rate, we consider a non-orthogonal multiple access (NOMA) scheme with imperfect channel state information on Eves. Fur-thermore, we design a robust precoding algorithm to maximize the achievable secrecy rate of legitimate ground user equipments, which satisfies the quality of service for each user, secure outage probability constraint and the NOMA decoding order between legitimate users. In contrast to the conventional total transmit power constraint, the algorithm is designed under joint total and per-beam transmit power constraints. We first combine the decomposition-based large deviation inequality, the arithmetic-geometric mean inequality with a penalty function iterative algorithm to solve the non-convex precoding problem, and further analyze the computational complexity of the algorithm. Simulation results verify the robustness and superiority of the proposed algorithm.

We investigate multi-user physical layer security assisted by an unmanned aerial vehicle (UAV) for multi-beam satellite communications in the presence of an eavesdropper (Eve) within the same beam. In particular, the UAV is exploited as a jammer that deliberately generates artificial noise to confuse Eve. To achieve a positive secrecy rate, we consider a non-orthogonal multiple access (NOMA) scheme with imperfect channel state information at the user and Eve. Specifically, we design a robust precoding algorithm to maximize the minimum achievable secrecy rate that satisfies the quality of service for each user and the NOMA decoding order between legitimate users in each beam. In addition, the algorithm is designed under joint total and per-beam transmit power constraints. We first combine the Bernstein-type inequality, the arithmetic-geometric mean inequality with a semi-definite relaxation iterative algorithm to solve the non-convex problem, and further analyze the complexity of the proposed precoding design. Simulation results show that the algorithm significantly improves the security performance.

This article investigates physical-layer security (PLS) of a typical wireless-powered communication (WPC) system with the aid of intelligent reflecting surface (IRS) in the presence of a passive eavesdropper for Internet of Things (IoT), and proposes three IRS-aided secure WPC modes. Specifically, in mode-I, the IRS is deployed between hybrid access point (HAP) and wireless user (U) for co-located power station (PS) and access point (AP). In mode-II, the IRS is deployed between AP and U for separate PS and AP, while in mode-III, the IRS is deployed between PS and U for separate PS and AP. For each mode, the optimal phase shift is designed to maximize the reception of energy and information at the legitimate receiver. We comprehensively analyze the performance of each mode, and derive the closed-form expressions of connection outage probability (COP), secrecy outage probability (SOP), and effective secrecy throughput (EST) for each mode, respectively. The theoretical analysis and simulation results reveal that from the perspective of reliability, mode-I can achieve the best COP with the increased number of IRS elements, while mode-II and mode-III have a similar COP. From the perspective of security, mode-II can achieve the best SOP with the increased number of IRS elements, while mode-I and mode-III have a similar SOP. Moreover, under the condition of small transmission power at HAP/PS or small number of IRS elements, mode-I has the best EST, while as the power or the number increases, the EST of mode-II becomes the best one.

This paper investigates the limit covert rate of the backscatter communication systems based on undecodable ambient radio frequency (RF) signals over additive white Gaussian noise channel. In the considered network, source node Alice expects to transmit information to receiver Bob without being detected by warden Willie, by backscattering undecodable ambient RF signals. In this case, it is challenging for Bob to recover the information from Alice, since the undecodable signals result in both unknown additive and multiplicative interference. A subtle communication strategy is proposed to alleviate the influences of the interference, by which we prove that no matter Willie can or cannot decode the information from the RF source and then eliminate its interference, the limit covert rate is subject to the well-known square root law (i.e.,O(√n) bits pernchannel uses). This interesting result means that even if the RF source is a cooperative node of Willie (e.g., a jammer deployed by Willie to restrict Alice from active transmission), Alice can still covertly and reliably transmit information to Bob by backscattering the ambient RF signals (e.g., the malicious jamming signals).

Existing symbol timing recovery (STR) cannot simultaneously meet the performance requirements of broadband satellite internet for throughput, convergence speed, convergence accuracy, and implementation complexity. Focusing on burst single-carrier communications widely used in broadband satellite systems, we proposed a parallel doubly fed STR algorithm combining feedforward and feedback loop, in which the frequency-domain (FD) prefilter is also used to improve the algorithm’s anti-self-noise capability. The corresponding field programmable gate array (FPGA) implementation with low complexity and highly parallel architecture is then accomplished. Simulation results show that the performance degradation caused by the proposed algorithm is less than 0.03 dB compared with the ideal performance when uncoded bit error rate (BER) equals 1e-4 and 64 quadrature amplitude modulation (QAM) modulation is considered. FPGA verification based on the XC7VX690T chip also shows that with 64 parallel inputs and 64-QAM modulation, the throughput rate of information bit can reach 19.2 Gb/s for our design with utilization of 17% look-up tables (LUTs) and 20% digital signal processing (DSP), respectively.

With the rapid development of various services in wireless communications, spectrum resource has become increasingly valuable. Faster than Nyquist (FTN) signaling, proposed in the 1970s, is a promising paradigm for improving spectrum utilization. This paper proposes the variable-packing-ratio (VPR)-based transmissions for high spectrum efficiency (SE) and security, respectively. Aided by deep learning (DL)-based estimation, the proposed scheme for high SE can achieve a higher capacity than the conventional Nyquist-criterion transmission with negligible modification to existing communication paradigms (e.g., spectrum allocation or frame structure). More importantly, for VPR-based secure transmission, a dynamic generation scheme is proposed to produce randomly distributed positions to switch the packing ratio, which can effectively avoid detections and attacks. In addition, we propose a simplified DL-based packing ratio estimation for both of these two scenarios so that the receiver can estimate the packing ratio without any in-band or out-band control messages. Simulation results show that the proposed simplified estimation achieves nearly the same accuracy and convergence speed as the original multi-branch fully-connected structure with a complexity reduction of 20 folds. Finally, we derive the SE of the proposed VPR transmission under different channels. The numerical results validate the correctness of the derivation and demonstrate the SE gains of the VPR scheme beyond conventional Nyquist transmission.

Nonorthogonal multiple access (NOMA) assisted semi-grant-free transmission admits grant-free users to access the channels otherwise solely occupied by grant-based users, and has been recently attracting considerable attention in terms of accommodating massive connectivity and reducing access delay in Internet of Things (IoT). In this work, we investigate the security of semi-grant-free NOMA transmission in the presence of passive and active eavesdropping attacks. In particular, for the scenario-I with strong grant-based user and weak grant-free users, the scenario-I-based maximal user scheduling (IbMUS) and scenario-I-based optimal user scheduling (IbOUS) schemes are proposed to combat the passive and active eavesdropping, respectively. For the scenario-II with weak grant-based user and strong grant-free users, two parallel schemes, namely, the scenario-II-based maximal user scheduling (IIbMUS) and scenario-II-based optimal user scheduling (IIbOUS) schemes, are proposed to combat the passive and active eavesdropping, respectively. These proposed schemes enhance the security by scheduling a grant-free user with maximal main channel capacity/maximal secrecy capacity to access the NOMA channel on the premise of ensuring the grant-based user’s Quality of Service. Based on these proposed schemes, the exact secrecy outage probability (SOP) are analyzed to evaluate the system performance. The simulation results validates the theoretic analysis and the superiority of the proposed schemes. The IbOUS and IIbOUS schemes can achieve better performance than the IbMUS and IIbMUS schemes owing to the use of active eavesdropper’s channel state information (CSI). The SOP achieved by the proposed schemes can be further improved with the increasing number of grant-free users and decreasing target rate (or target secrecy rate).

Estimating the location parameters of moving target is an important part of intelligent surveillance for the Internet of Vehicles (IoV). Satellite has the potential to play a key role in many applications of space–air–ground-integrated networks (SAGINs). In this article, a novel passive location parameter estimator using multiple satellites for the moving aerial target is proposed. In this estimator, the direct wave signals in reference channels are first filtered by a band-pass filter, followed by a sequence cancelation algorithm to suppress the direct-path interference and multipath interference. Then, the fourth-order cyclic cumulant cross ambiguity function (FOCCCAF) of the signals in the reference channels and the four-weighted fractional Fourier transform FOCCCAF (FWFRFT-FOCCCAF) of signals in the surveillance channels are derived. Using them, the time difference of arrival (TDOA) and the frequency difference of arrival (FDOA) are estimated and the distance between the target and the receiver and the velocity of the moving aerial target are estimated by using multiple satellites. Finally, the Cramer–Rao lower bounds of the proposed location parameter estimators are derived to benchmark the estimator. The simulation results show that the proposed method can effectively and precisely estimate the location parameters of the moving aerial target.

Identification of transmit-antenna number is of importance in cognitive Internet of Things (IoT) with multiple-input–multiple-output (MIMO). Previous studies on transmit-antenna number detection only consider Gaussian noise and ignore impulsive interference. In the practical wireless communication, impulsive interference may exist due to low-frequency atmospheric noise, multiple access, and electromagnetic disturbance. Such interference can usually be modeled as symmetric alpha stable ($S\alpha S$), which cause the performance degradation of conventional algorithms based on the Gaussian model. In this article, we present a novel scheme to detect the transmit-antenna number for MIMO systems in cognitive IoT, assuming that signals are corrupted by both$S\alpha S$interference and Gaussian noise. We first introduce a new approach to characterize the generalized correlation matrix (GCM), and provide its bound with$S\alpha S$interference. Then, the discriminating feature vector is constructed by utilizing the higher order moments (HOMs) of eigenvalues of the GCM. Finally, an advanced clustering algorithm is employed to detect the transmit-antenna number, using the cluster where the minimum eigenvalue is located. The proposed algorithm avoids the need fora prioriinformation about the transmitted signals, such as coding mode, modulation type, and pilot patterns. Simulation experiments demonstrate the feasibility of the proposed transmit-antenna number detection scheme in MIMO systems with Gaussian noise and$S\alpha S$interference.

The next-generation cellular system operating in millimeter-wave (mm-Wave) frequencies requires different signal processing schemes from the legacy LTE system. Among these, beam management aligns the transmitter-receiver pairs with narrow beams and serves as an essential initial acquisition procedure. This paper introduces a novel angle-based downlink precoding strategy, including beam selection and user scheduling for a full dimension (FD) MIMO-OFDM system. The highly directional mm-Wave channel allows the system to perform user/beam scheduling rather than pure user scheduling during the precoding process. A beam-based receive matrix eliminates the remaining intra-cell interference caused by overlapped beams. The performance analysis proves the superiority of the proposed precoding and scheduling strategies over the conventional technique.

We investigate the secrecy transmission of uplink non-orthogonal multiple access (NOMA) with the aid of energy harvesting (EH) jammers. During each time frame, communication is divided into two phases. At the first phase, the base station (BS) transfers wireless power to EH receivers (EHRs). At the second phase, users perform uplink NOMA transmission to BS, while one of EHRs is selected as a friendly jammer that uses the energy harvested from the previous phase to emit the artificial noise for confusing the eavesdropper. In terms of the requirement of channel state information (CSI), we propose three friendly EH jammer selection schemes, namely random EH jammer selection (REJS) scheme without the requirement of any CSI, maximal EH jammer selection (MEJS) scheme with the CSI between BS and each EHR, and optimal EH jammer selection (OEJS) scheme where both the CSIs from BS to EHRs and from EHRs to the eavesdropper need to be known. Analytical closed-form expressions for the connection outage probability (COP), secrecy outage probability (SOP) and effective secrecy throughput (EST) are derived to evaluate the system performance achieved by the proposed schemes, respectively. Also, the asymptotic analysis is provided to gain further insights. The analytical and numerical results indicate that the proposed schemes can realize better secrecy performance than conventional scheme without an EH jammer. Both the secrecy diversity orders of the REJS and MEJS schemes are one while the OEJS scheme can achieve a full secrecy diversity order. Furthermore, owing to the impact of connection outage, the three schemes converge to the same EST floor with the increase of signal-to-noise ratio (SNR).

With the proliferation of mobile access services and wireless devices, spectrum resources are increasingly becoming scarce. Industrial wireless sensor networks may have to share frequency bands with other systems and suffer from considerable interference. To address that, industrial cognitive radio networks (ICRNs) were developed for effective spectrum sharing, where signal classification is a fundamental and important technology, especially for industrial wireless devices, which need to identify suspicious transmissions. In this article, a novel framework of signal intelligent classification is proposed based on deep learning networks in ICRNs. In the proposed framework, wireless signals will be preprocessed first by Choi-Williams distribution time-frequency analysis and represented by two-dimensional time-frequency images. Then, features of wireless signals are extracted through stack hybrid autoencoders (SHAEs). To accommodate general cases, we design multiple signal classification methods, including unsupervised, semisupervised, and supervised methods, which are processed by Softmax function, semisupervised linear discriminant function, and Fisher discriminant function, respectively. Finally, simulation studies are conducted and the corresponding simulation results show that the proposed framework is able to learn hierarchical features accurately and achieve excellent signal classification performance. Moreover, it can effectively overcome the negative impact caused by feature parameters uncertainty.

Satellite industrial Internet of Things (IIoT) plays an important role in industrial manufactures without requiring the support of terrestrial infrastructures. However, due to the scarcity of spectrum resources, existing satellite frequency bands cannot satisfy the demand of IIoT, which have to explore other available spectrum resources. Cognitive satellite networks are promising technologies and have the potential to alleviate the shortage of spectrum resources and enhance spectrum efficiency by sharing both spectral and spatial degrees of freedom. For effective signal estimations, multiple features of wireless signals are needed at receivers, the transmissions of which may cause considerable overhead. To mitigate the overhead, part of parameters, such as modulation order, constellation type, and signal to noise ratio (SNR), could be obtained at receivers through signal estimation rather than transmissions from transmitters to receivers. In this article, a grid method is utilized to process the constellation map to obtain its equivalent probability density function. Then, binary feature matrix of the probability density function is employed to construct a cost function to estimate the modulation order and constellation type for multiple quadrature amplitude modulation (MQAM) signal. Finally, an improved M2M∞method is adopted to realize the SNR estimation of MQAM. Simulation results show that the proposed method is able to accurately estimate the modulation order, constellation type, and SNR of MQAM signal, and these features are extremely useful in satellite-based IIoT.

In industrial sensor networks, complex industrial environments may be encountered leading to a mix of signals of different types. Complicated interference caused by mixed signals on industrial equipments may significantly degrade the classification rate of signals, which may result in a long training time in order to extract features. In addition, with limited channel resources, it is difficult to make the global optimal decision in industrial distributed wireless sensor networks. To address this problem, a signal classification method using feature fusion is proposed for industrial Internet of Things in this article. In the proposed method, the received signals of nodes are processed by frequency reduction and sampling pretreatment, based on which intelligent representations of signals are obtained. Using federated learning, the data samples are trained with the feature fusion network. Moreover, the trained deep learning network is used on each sensor node to classify signals, the results of which will be transmitted to aggregation center. In the aggregation center, the improved evidence theory method is used to aggregate the recognition results of each sensor node to achieve the final classification. Simulation shows that the proposed method has excellent classification performances. Notably, it is not required for the proposed method to transmit signals from nodes to the aggregation center, which could effectively protect the privacy of industrial information.

In this paper, a backscatter cooperation (BC) scheme is proposed for non-orthogonal multiple access (NOMA) downlink transmission. The key idea is to backscatter the surplus power of the received downlink signals at one user to enhance the reception of the user who cannot recover its information. To evaluate the performance of the proposed BC-NOMA scheme, three benchmark schemes are introduced, which include the non-cooperation (NC)-NOMA scheme, the conventional relaying (CR)-NOMA scheme, and the incremental relaying (IR)-NOMA scheme. For all these schemes, the outage performance, the expected rate, and the diversity-multiplexing trade-off (DMT) performance are analyzed. Additionally, the optimal power allocation to maximize the expected rate of the BC-NOMA scheme in the high signal-to-noise ratio region is derived. The theoretical results show that the proposed BC-NOMA can enhance both transmission reliability (outage performance) and transmission effectiveness (expected rate) compared with NC-NOMA. Furthermore, representative numerical results are presented to validate the theoretical results. It is shown that unlike the two relaying-based cooperative schemes (CR/IR-NOMA), which improve the outage performance at the cost of transmission rate, the proposed BC-NOMA scheme can enhance the transmission reliability without impairing the spectrum efficiency, which makes backscattering an appealing solution to cooperative NOMA downlinks.

In this paper, a downlink (DL) precoding scheme is introduced for time-division-duplex (TDD) multi-cell multi-user 3D massive MIMO/full-dimension MIMO (FD-MIMO) systems. A pre-beamformer based on uplink direction-of-arrival (DoA) is incorporated with interference alignment (IA) scheme to provide more degrees of freedom for each cell. We analyze the feasible conditions of applying IA schemes and provide the corresponding precoding schemes for different inter-cell interference scenarios. Simulation results show that the introduced IA-DoA-based multi-cell multi-user precoding and power allocation scheme significantly outperform the existing IA-based precoding strategies for FD-MIMO systems.

A backscatter cooperation (BC) mechanism is pro-posed for power-domain non-orthogonal multiple access (NOMA) downlink transmission. The key idea is to enable one user to split and then backscatter part of its received signals to improve the reception at another user. To evaluate its performance, three benchmark schemes are introduced. They are non-cooperation (NC)-NOMA, conventional relaying (CR)-NOMA, and incremental relaying (IR)-NOMA. For all these schemes, the analytical expressions of the minimum total power to avoid information outage are derived, based on which their respective outage performance, expected rates, and diversity-multiplexing trade-off (DMT) are investigated. Analytical results show that the proposed BC-NOMA strictly outperforms NC-NOMA in terms of all the three metrics. Furthermore, theoretical analyses are validated via Monte-Carlo simulations. It is shown that compared with CR/IR-NOMA, only the proposed BC-NOMA scheme can enhance the transmission reliability without impairing the transmission rate.

Faster‐than‐Nyquist (FTN) signalling is regarded as a promising technology in satellite communications for the past few years, however, existing inter‐symbol interference (ISI) elimination algorithms for FTN signalling cannot eliminate the linear distortion caused by the input‐multiplexing and output‐multiplexing filters, which are very common in satellite communications. On the strength of the fractionally‐spaced equaliser (FSE), the authors propose a precoding‐based frequency‐domain linear distortion equaliser (PFLDE) to eliminate the above‐mentioned linear distortion in FTN systems. On the one hand, by virtue of fast Fourier transform (FFT) and inverse FFT, the proposed PFLDE lends itself naturally to high‐throughput parallel architectures, which are quite essential in high throughput satellite communications. On the other hand, the mean square error performance of the proposed PFLDE is superior to that of the existing time‐domain FSEs. Furthermore, combining PFLDE with the existing ISI elimination algorithms for FTN signalling, the satisfactory bit error ratio performance can be obtained.

A symbol‐based multi‐layer iterative successive interference cancellation (MLISIC) algorithm is proposed to eliminate the inter‐symbol interference (ISI) for faster‐than‐Nyquist signalling. The computational complexity of the proposed MLISIC algorithm is much lower than most existing block‐based estimation algorithms. By comparison with existing symbol‐based algorithms, the proposed MLISIC algorithm has higher estimation accuracy. Furthermore, by means of utilising more accurate symbols and elaborate length of successive interference cancellation, an improved MLISIC (IMLISIC) algorithm is presented to further promote the estimation accuracy. Simulation results show in mild ISI cases, the proposed MLISIC and IMLISIC algorithms can approximate the theoretical performance even using 256‐amplitude phase‐shift keying which is adopted in digital video broadcasting‐satellite‐second generation extension, i.e. bit error rate (BER) performance degradation is about 0.03 dB when the signal‐to‐noise ratio is high. In other words, using the proposed MLISIC and IMLISIC algorithms in mild ISI cases, the spectrum efficiency can be improved with negligible BER performance degradation. Besides, compared with existing symbol‐based algorithms, the greater BER performance improvement can be achieved under severer ISI circumstances.

The emerging cognitive radio-based Internet-of-Things (CR-IoT) network provides a novel paradigm solution for IoT devices to efficiently utilize spectrum resources. Spectrum sensing is a critical problem in the CR-IoT network which has been investigated extensively under the Gaussian noise/interference. Since most of the interference in an IoT network is non-Gaussian, in this article, we introduce a novel spectrum sensing method for CR-IoT with additive Gaussian mixture noise/interference. The introduced method maps the observation signal matrix from the original input space to a high-dimensional feature space by a nonlinear Gaussian kernel function and then constructs a kernelized test statistic in the feature space. The approximate analytical expressions of the false alarm and detection probability of the proposed scheme are derived under Gaussian mixture noise, and the decision threshold can be determined according to false alarm probability. The simulation results show that the introduced multiple-input-multiple-output (MIMO) spectrum sensing method achieves good performance under Gaussian mixture noise/interference and significantly outperforms existing detectors.

We investigate physical layer security of an uplink NOMA system consisting of one base station, multiple users and one eavesdropper. During each uplink transmission, two users are paired to perform NOMA and another user is opportunistically selected from the remaining idle users to act as a friendly jammer to emit artificial noise for confusing the eavesdropper. To enhance the transmission security for the system, we propose two friendly jammer selection aided uplink NOMA transmission schemes, namely random jammer selection aided uplink NOMA transmission (RJS-UNT) scheme without knowing the eavesdropper's channel state information (CSI), and optimal jammer selection aided uplink NOMA transmission (OJS-UNT) scheme where the eavesdropper's CSI is available. For comparison purpose, a non-jammer selection aided uplink NOMA transmission (NJS-UNT) scheme is also considered. Analytical closed-form expressions for the secrecy outage probability (SOP) are derived to evaluate the secrecy performance achieved by the proposed schemes. Also, the asymptotic SOPs are provided to obtain further insights. The analysis and simulation results indicate that the schemes converge to SOP floors with the increasing SNR, while the floors achieved by the RJS-UNT and OJS-UNT schemes are significantly lower than that achieved by the NJS-UNT scheme, showing the security advantage of the proposed schemes.

Blind estimation of parameters for M-ary frequency-shift-keying (M-FSK) signals is great of importance in intelligent receivers. Many existing algorithms have assumed white Gaussian noise. However, their performance severely degrades when grossly corrupted data, i.e., outliers, exist. This article solves this issue by developing a novel approach for parameter estimation of M-FSK signals in the presence of alpha-stable noise. Specifically, the proposed method exploits the generalized first- and second-order cyclostationarity of M-FSK signals with alpha-stable noise, which results in closed-form solutions for unknown parameters in both time and frequency domains. As a merit, it is computationally efficient and thus can be used for signal preprocessing, symbol timing estimation, signal and noise power estimation. Furthermore, substantial theoretical analysis on the performance of the proposed approach is provided. Simulations demonstrate that the proposed method is robust to alpha-stable noise and that it outperforms the state-of-the-art algorithms in many challenging scenarios.

The key idea of non-orthogonal multiple access (NOMA) is to serve multiple users in the same resource block to improve the spectral efficiency. Whereas due to the resource sharing, a security flaw of NOMA emerges in the presence of internal untrusted users, especially untrusted near users who are closer to the base station and can easily access the confidential information for paired far users. To mitigate the flaw, in this paper, we investigate the reliable and secure transmission of NOMA systems with untrusted near users, and propose joint beamforming and power allocation (JBP) scheme for the scenario. Meanwhile, from security point of view, we extend to a worse-case scenario where both untrusted near users and external eavesdroppers exist, and propose joint artificial noise aided beamforming and power allocation (JANBP) scheme to achieve a reliable and secure transmission for the scenario. The exact and asymptotic closed-form expressions of secrecy outage probability (SOP) for the two scenarios are derived to evaluate the secrecy performance achieved by the proposed schemes, respectively. The analysis and simulation results show the superiority of the proposed JBP and JANBP schemes in terms of combating internal and external eavesdropping, and also indicate the two schemes can achieve the same SOP at high SNR.

Underlay cognitive radio (CR) holds the promise to address spectrum scarcity and let industrial wireless sensor networks obtain spectrum extension from shared frequency band resources. However, underlay CR devices should be capable of properly adjusting wireless transmission parameters according to the sensing of wireless environments. To realize the goal, in this article, two different signal-to-noise ratio (SNR) estimation methods are proposed for time-frequency overlapped signal estimations in the underlay CR-based industrial Internet of Things (IoT). In the first method, normalized higher order cumulant equations and the theoretical value of normalized higher order cumulants are adopted to estimate the SNR of component signals and the SNR of received signals. In the second one, the power of each component signals and the received signals is estimated based on the second-order time-varying moments. For the performance analysis, the Cramer-Rao lower bound of the SNR estimation for the time-frequency overlapped signals is derived. Simulation results show that the proposed method based on normalized higher order cumulants not only can effectively estimate the SNR of the time-frequency overlapped signals, but also has the strong robustness to the spectrum overlapped rate and the hybrid power ratio. The proposed method with second-order time-varying moments is able to accurately estimate the SNR of the time-frequency overlapped signals effectively, especially in the low-SNR region. These features are extremely useful in the industrial IoT, which usually operate in low-SNR regimes.

In this paper, an impartial simultaneous wireless information and power transfer (SWIPT)-assisted cooperation mechanism is proposed for a non-orthogonal multiple access (NOMA) downlink scenario. The key idea of the proposed impartial user cooperation mechanism (IUCM) is that not only the cell-center user but also the cell-edge user applies the power-splitting architecture and utilizes the harvested energy to forward the other user's information. Analytical results show that the proposed IUCM outperforms the traditional partial cooperation mechanism in terms of outage probability, diversity order and diversity-multiplexing trade-off (DMT). For comparison, the proposed IUCM is further incorporated into an orthogonal frequency-division multiple access (OFDMA) framework, which is shown to preserve the same diversity order, while has a worse but more flexible DMT performance compared with the IUCM in the NOMA framework. Furthermore, a classic non-linear energy harvesting model is introduced, based on which the outage probability, diversity order and DMT performance of the proposed IUCM and the conventional mechanism are analyzed. Finally, representative numerical results are given to validate our theoretical analysis.

A downlink user scheduling algorithm based on the pricing scheduling factor is proposed for the established relay‐assisted massive multiple input multiple output (MIMO) model, which represents the typical remote cell with multiple relays and a massive MIMO base station. Different from the traditional scheduling algorithms, the authors' proposed scheduling algorithm simultaneously takes account of the strength of the desired signal and interference, in which the proposed scheduling factor takes interference strength as the price to select appropriate users. An analysis on the optimal precoding vector is given by assuming each relay adopts equal gain transmission (EGT). According to the analysis, a non‐cooperative solution based on the phase difference of EGT is proposed to search the optimal transmission direction of EGT with low complexity. An analytical upper bound of system sum rate is also obtained. Simulation results indicate that the proposed scheduling algorithm has excellent sum rate performance and slight rate degradation compared with the brute‐force search algorithm.

Recently, vehicular ad hoc networks (VANETs) have been attracting significant attention for their potential for guaranteeing road safety and improving traffic comfort. Due to high mobility and frequent link disconnections, it becomes quite challenging to establish a reliable route for delivering packets in VANETs. To deal with these challenges, an artificial spider geographic routing in urban VAENTs (ASGR) is proposed in this paper. First, from the point of bionic view, we construct the spider web based on the network topology to initially select the feasible paths to the destination using artificial spiders. Next, the connection-quality model and transmission-latency model are established to generate the routing selection metric to choose the best route from all the feasible paths. At last, a selective forwarding scheme is presented to effectively forward the packets in the selected route, by taking into account the nodal movement and signal propagation characteristics. Finally, we implement our protocol on NS2 with different complexity maps and simulation parameters. Numerical results demonstrate that, compared with the existing schemes, when the packets generate speed, the number of vehicles and number of connections are varying, our proposed ASGR still performs best in terms of packet delivery ratio and average transmission delay with an up to 15% and 94% improvement, respectively.

Based on the field-programmable gate array (FP-GA) structure, a versatile transmission loss tester for wireless communications, especially satellite communications, is developed to obtain the bit error rate (BER) and transmission loss efficiently. The hardware of the tester can be treated as an integrated radio frequency (RF) transmission system with an embedded additive white Gaussian noise (AWGN) module. The FPGA-based RF system can generate at most 10 independent channels (ICs) with multiple rolling factors. Multiple symbol rates from 2 Ksps to 34 Msps can be supported with an appropriate multistage up-sampling processing. Furthermore, at most 640 sub-channels can be generated with the help of poly-phase filter banks and a well-designed FPGA realization of quadrature phase shift keying (QPSK) modem. The precomputation and test results show that a high dynamic range of transmitting and receiving signal levels can be supported. In addition, the expected transmission loss at one specific BER can be easily observed and acquired with the help of an integrated automated monitoring software developed by Qt development tool.

A simplified blind equalization algorithm, which can substantially reduce the complexity of hardware implementation of neighborhood-assisted symbol-based decision (N-SBD) algorithm, is proposed for 4096-QAM systems. Two main strategies are adopted in order to achieve our goals. On the one hand, the step function is used to approximate the weighting factor in the conventional N-SBD algorithm for avoiding the complicated exponential calculations. On the other hand, by utilizing the equidistant characteristics for the adjacent symbol coordinates, we derive the formula of the error function again, thus significantly reducing the number of multipliers in implementation. The analysis further shows that, for 4096-QAM signals, the proposed algorithm greatly reduces the implementation complexity at the cost of reducing the convergence speed slightly, whereas it can maintain the mean square error (MSE) performance of the steady-state residual error when compared with the conventional N-SBD algorithm. Simulation results also indicate that both the convergence speed and the steady-state residual error of the proposed algorithm are superior to other blind equalization algorithms, such as the multi-modulus algorithm (MMA) and constellation matched error-based MMA (CME-MMA).

As known, receivers with in-phase and quadrature-phase (I/Q) down conversion, especially direct-conversion architectures' always suffer from I/Q imbalance. I/Q imbalance is caused by amplitude and phase mismatch between I/Q paths. The performance degradation resulting from I/Q imbalance can not be mitigated with simply higher signal to noise ratio (SNR). Thus, I/Q imbalance compensation in digital domain is critical. There are two main contributions in this paper. Firstly, we proposed a blind estimation algorithm for I/Q imbalance parameters based on joint first and second order statistics (FSS) which has a lower complexity than conventional Gaussian maximum likelihood estimation (GMLE). This can be used for further precessing such as equalization in presence of receiver IQ imbalance. In addition, we find out the reason of error floor in conventional I/Q imbalance compensation method based on conjugate signal model (CSM). The proposed joint first order statistics and conjugate signal model (FSCSM) compensation algorithm can reach the ideal bit error rate (BER) performance.

A simplified polarity decision carrier recovery (CR) algorithm is proposed by using the characteristics of 4096-QAM constellation. The proposed scheme, which has the better tradeoff between the performance and the complexity by using a simplified polarity decision phase detector (PD), includes three working modes. The initial frequency offset estimator (IFOE) is firstly applied to estimate the frequency offset in open-loop mode, then the phase-frequency detector (PFD) tracks and compensates the small frequency error in closed-loop mode. A simple decision-directed (DD) PD is finally used for fine phase tracking. Compared with the conventional polarity decision PD, the polarity decision PD in our algorithm needs fewer multipliers, whereas the proposed algorithm can slightly accelerate the convergence speed and maintain the estimation performance. Results show that, the time required for loop convergence is less than 105symbol periods within the range of the normalized frequency offset between -0.09 and 0.09 for 4096-QAM.

Without channel state information at the users and relay node, a non‐coherent transmission scheme for the two‐way relaying systems is investigated in this study. At the relay node, the authors first detect the uplink data with non‐coherent maximum likelihood receiver by fully utilising the large receiving freedom of relay's large‐scale antennas. Channel estimations can also be obtained by treating the detected uplink data as pilot symbols. Then, the relay node forwards the detected data by using beamforming. To assure the reliable detection of the users' transmitted symbols non‐coherently, the authors propose a transmitting constellation design with the idea of searching an optimal angle for rotating one user's constellation. Specially, for M ‐PSK constellations, they derive the optimal rotation angle, which is highly consistent with the exhaustive searching results. In addition, they also analyse the lower bound of channel estimations in terms of normalised mean square error (NMSE). From simulation results, the proposed non‐coherent transmission scheme achieves considerable error performance, and the NMSE lower bounds of channel estimations are also tight when the number of relay's antennas approaches to be large.

For the design and performance evaluation of potential massive multiple input and multiple output (MIMO) related algorithms, accurate channel models are indispensable. Spherical wavefront and array non-stationarity due to physically large antenna array are two new characteristics specific to massive MIMO propagation. In this paper, spherical wavefront effects can be well characterized by a predefined two-dimensional multi-confocal ellipse scattering geometry as in reference [1] and a 9- state Markov process is developed to capture the channel behaviors by array non-stationarity. Meanwhile, the associated approach to derive the state transition probabilities of the Markov process based on the outfield measurements is detailed. Finally, simulation results verify the validity of our proposal.

Traditional vector orthogonal frequency division multiplexing (V‐OFDM) can obtain both multi‐path diversity and outage gain by transforming an inter‐symbol interference (ISI) channel into multiple ‘ISI‐free’ channel vectors. To achieve full multi‐path diversity and acquire better outage performance, a low‐complexity precoding scheme combined with simple minimum mean square error (MMSE) equalisation for V‐OFDM system is proposed in this study. First, the upper mutual information bound of the V‐OFDM system is derived with channel state information at transmitter. Based on the upper bound, an optimal precoding scheme for V‐OFDM is presented. Meanwhile, the closed‐form and asymptotic expressions on outage probability of the proposed scheme are derived. Simulations show that this low‐complexity scheme can achieve full multi‐path diversity and result in lower outage probability than the traditional V‐OFDM scheme. Besides, the proposed scheme in ISI fading channel is capable of approaching the upper bound with <0.1 bits/s/Hz performance gap and improving average channel capacity with 2 bits/s/Hz over the traditional V‐OFDM scheme.

Based on the criterion of maximising the end‐to‐end receiving signal‐to‐noise power ratio, a dual‐antenna selection scheme combining with distributed space–time block code is proposed for two‐way relaying networks with amplify‐and‐forward protocol in Rayleigh fading channels. To facilitate the performance analysis, the authors derive the lower bound and asymptotic expressions for the network outage probability performance. Moreover, a concise solution for optimal power allocation is also determined to minimise the outage probability under a total power constraint. From the asymptotic outage probability analysis, the authors demonstrate that the proposed dual‐antenna selection scheme can achieve full outage diversity. Finally, numerical results verify the accuracy of the authors’ analysis. Notably, the proposed scheme achieves competitive performance improvement compared with the beamforming scheme and the existing antenna selection schemes in the state of the arts.

Considering a dual-hop energy-harvesting (EH) relaying system, this paper advocates novel relaying protocols based on adaptive time-switching (TS) for amplify-and-forward and decode-and-forward modes, respectively. The optimal TS factor is first studied, which is adaptively adjusted based on the dual-hop channel state information (CSI), accumulated energy, and threshold signal-to-noise ratio (SNR), to achieve the maximum throughput efficiency per block. To reduce the CSI overhead at the EH relay, a low-complexity TS factor design is presented, which only needs single-hop CSI to determine the TS factor. Theoretical results show that, in comparison with the conventional solutions, the proposed optimal/low-complexity TS factor can achieve higher limiting throughput efficiency for sufficiently small threshold SNR. As the threshold SNR approaches infinity, the throughput efficiency of the proposed optimal/low-complexity TS factor tends to zero in a much slower pace than that of the conventional solutions. Simulation results are presented to corroborate the proposed methodology.

This paper quantifies the impact of correlated fading on secure communication of multiple amplify-and-forward (AF) relaying networks. In such a network, the base station (BS) is equipped with multiple antennas and communicates with the destination through multiple AF relays, while the message from the relays can be overheard by an eavesdropper. We focus on the practical communication scenario, where the main and eavesdropper's channels are correlated. In order to enhance the transmission security, transmit antenna selection is performed at the BS, and the best relay is chosen according to the full- or partial-relay selection criterion, which relies on the dual-hop relay channels or the second-hop relay channels, respectively. For these criteria, we study the impact of correlated fading on the network secrecy performance, by deriving an analytical approximation for the secrecy outage probability and an asymptotic expression for the high main-to-eavesdropper ratio. From these results, it is concluded that the channel correlation is always beneficial to the secrecy performance of full relay selection. However, it deteriorates the secrecy performance if partial-relay selection is used, when the number of antennas at the BS is less than the number of relays.

For the design, performance evaluation, and optimization of potential 3-D multiple input and multiple output (3-D MIMO) algorithms, an accurate stochastic channel model is indispensable. Simultaneously, it is desirable for the new 3-D MIMO channel model to be a further expansion of already well developed 2-D MIMO channel models to allow easy implementation and facilitate possible $3^{rd}$ generation partnership project standardization. This paper first shows our recent outfield channel measurement campaigns in urban macrocell scenarios with a planar antenna array and a crown-shaped antenna array installed on the base station and the user sides, respectively. A comprehensive methodology from the statistical analysis perspective to characterize the 3-D MIMO channel, particularly, in the elevation domain, is then elaborated upon. The framework of the new approach coincides with mainstream parametric stochastic models. Moreover, it is observed that, by recalculating the statistics of the large scale parameters as well as their cross-correlation matrix to rectify existent non-positive definite problem, adding distance dependent elevation angular spread and introducing a mixture of Von Mises Fisher distributions to describe the interdependence between azimuth and elevation, the accuracy of current standardized 3-D channel models can be improved upon. Finally, numerical results verify the validity of our proposal.

This paper proposes a selective AF-OFDM (Amplify-and-Forward, Orthogonal Frequency Division Multiplexing) relaying protocol, in which selective relaying policy is adequately utilized to improve the spectrum efficiency of cooperative multi-carrier transmission, and addresses the power minimization problem subject to a target quality of service (QoS) constraint for corresponding battery-operated systems. By transforming the original power minimization issue into a two-stage problem, i.e., a power loading subproblem and a selective relaying policy decision subproblem, an energy efficient power control (PC) technique is proposed. Specifically, the binary selective relaying policies are determined for each subcarrier based upon channel state information (CSI), while power loading can be mathematically solved by employing standard Lagrange techniques, leading to analytical solutions for individual transmit powers at the source and the relay. In order to further improve the energy efficiency, an independent \emph{min-min} relay selection policy is investigated by making use of available diversity of the multiple-relay channel. Numerical results illustrate the superiority of the proposed selective AF-OFDM relaying protocol and validate the efficiency of our proposed algorithms. It is shown that with PC, the proposed selective AF-OFDM relaying can significantly reduce the system power consumption, and the \emph{min-min} relay selection policy is more appropriate than the conventional \emph{max-min} strategy for our transmission protocol.

A general distributed multi-antenna two-way relaying network with multiple relays is considered in this paper. We first obtain a tight lower bound of pairwise error probability (PEP) of a maximum likelihood detector for the general distributed linear dispersion code for a half-duplex amplify-and-forward two-way relaying network (TWRN) consisting of two sources with each having single antenna and N relays with each having two antennas. Furthermore, by jointly considering signal precoding at the sources and signal processing at the relays, a general distributed concatenated recursive Alamouti-circulant space-time block code is proposed for the considered TWRNs. Our design ensures that the equivalent channel matrices at both source nodes are the so-called the recursive Alamouti-circulant matrices, with each block being a product of the two Alamouti channel matrices. Based on a lower-upper bound strategy and an induction method, asymptotic PEP formula is attained to show that given the optimal angle rotation matrix and the precoding matrix, the code can meet the lower bound of the diversity gain, as well as the maximum coding gain. In addition, the proposed rate one code turns to be effectively decodable.

Two opportunistic transmission schemes, i.e., joint user-relay selection with beamforming (JURS-BF) and joint user-relay selection with antenna selection (JURS-AS), are proposed and analyzed for multi-user multi-relay bidirectional relaying networks (BRNs) composed of one N-antenna base station (BS)/ access point (AP), M single-antenna users, and K single-antenna relays. In particular, by considering the rate asymmetry between the BS/AP and the users, joint user-relay selection is tackled with beamforming and antenna selection to combine the benefits of multi-antenna diversity, multi-relay diversity, and multi-user diversity. To characterize the performance of the proposed JURS-BF and JURS-AS schemes, lower and upper bounds on the system outage probability are derived in closed form under Nakagami-m fading environment, followed by the diversity, coding gain analysis, and some discussions on the relay deployment. Our analytical results are verified through simulations, and it is proved that the proposed suboptimal schemes perform closely to the traditional outage-optimal counterparts while with much lower implementation complexity, which provides valuable insights into practical BRNs.

The multi-way relaying networks (MWRNs) are investigated, in which multiple users exchange their information with the help of a relay node. We constraint that all users form a single group to share information with each other by using half-duplex communication mode. For such networks, an universal linear dispersion space-time block code (STBC) is introduced based on amplify-and-forward (AF) relaying protocol. Furthermore, a lower bound of pairwise error probability (PEP) of maximum likelihood (ML) detector is first derived, which reveals that the best-achievable diversity gain function is determined by the signal to noise ratio ρ, the user number K and the antenna number of the relay M, i.e., In ρ/ρM(K-1). Specifically, we design a distributed quasi-orthogonal STBC for the MWRN with K = 3 and demonstrate that the design can obtain a larger diversity gain than those in the one-way and two-way relaying networks by Monte Carlo simulations.

This paper advocates a distributed role selection strategy to coordinate two-way relaying transmissions among three cooperative nodes. For such, the local channel state information comparison and decision feedback mechanism are merged into classical analog network coding (ANC) and time division broadcast (TDBC) protocols such that the cooperative role of each node can be designated in a distributed fashion. We refer to this distributed role selection rule as d-ROSE. In both ANC-based and TDBC-based two-way relaying scenarios, strict proof for the equivalence of d-ROSE and optimal ROSE is given, which indicates that albeit the different form, their final role decision is essentially the same. Outage analysis for the d-ROSE strategy is carried out and the scaling law of the system outage behavior at high signal-to-noise ratio (SNR) is characterized, which manifests that d-ROSE can enhance the system diversity gain to one-order higher relative to the ANC and TDBC protocols. It is also shown that d-ROSE can reduce the signaling overhead upto 60% to perform the outage-optimal role selection. Finally, the impacts of node placement on the outage performance as well as the average signaling overhead of d-ROSE are numerically evaluated and some useful conclusions are drawn.

In this paper, we consider a half-duplex amplify-and-forward two-way relaying network consisting of two sources with each having a single antenna and N relays with each having two antennas. For such a system with a general distributed linear dispersion code, a tight lower bound of pairwise error probability (PEP) of the maximum likelihood (ML) detector is derived, showing that diversity gain function cannot decay faster than lnNSNR/SNR2N, where SNR is signal to noise ratio. Particularly for N = 2b, a new distributed concatenated space-time block code (STBC) is proposed and its asymptotic PEP formula is attained, showing that the code presented in this paper achieves the maximum diversity gain, i.e., meeting the lower bound of the diversity gain function, as well as the maximum coding gain.

Utilizing the recently-developed unique factorization of signals and distributed Alamouti coding scheme, a distributed collaborative Alamouti space-time block code design is presented for a two-way amplify-and-forward (AF) relaying network, where both two sources and the relay are equipped with a single antenna. For such system, two asymptotic pairwise error probability (PEP) formulae are first derived for both fixed-gain AF and variable-gain AF over Rayleigh channels with the maximum likelihood detector. Then, subject to the constraints on a fixed transmission bit rate and unity average transmission energy, the optimal constellation combinations with the optimal energy-scales as the coefficients are attained by minimizing the dominant term of PEP. It is shown that the PEP and the average block error rate of the newly-designed code are superior to those of the conventional distributed Alamouti code.

Utilising the recently‐developed unique factorisation of signals and distributed Alamouti coding, a distributed collaborative space‐time block code design is presented for a two‐way amplify‐and‐forward (AF) relaying network, where all nodes are equipped with a single antenna. Two asymptotic pairwise error probability (PEP) formulae are firstly derived for both fixed‐gain AF and variable‐gain AF over Rayleigh channels with the maximum‐likelihood detector. Then, subject to the constraints on a fixed transmission bit rate and unity average transmission energy, the optimal constellation combinations with the optimal coefficients are attained by minimising the dominant term of PEP. It is shown that the PEP and the average block error rate of the newly‐designed code are superior to those of the conventional distributed Alamouti code while the prior still has linear‐decoding complexity.

A half-duplex amplify-and-forward two-way relay network consisting of two single-antenna sources and N relays with each having two antennas is considered in this paper. For such a system, a tight lower bound of pairwise error probability (PEP) of a maximum likelihood (ML) detector for any distributed linear dispersion code with a fixed average amplifier is derived, revealing that diversity gain function cannot decay faster than lnNSNR/SNR2N, where rm SNR is signal to noise ratio. Particularly for the network having two relays, a novel distributed quasi-orthogonal space-time block code (QO-STBC) is proposed with two significant advantages. One is that the equivalent channel matrices at both source nodes turn out to be the block-circulant matrices, with each block being a product of the two Alamouti channel matrices. The other is that the equivalent noises at the both source nodes are Gaussian and white. Therefore, like QO-STBC for a multi-antennas system, the proposed code for the relay system still maintains low-decoding complexity for the ML detector. Asymptotic PEP formula is attained to show that the proposed code enables the optimal diversity gain function, i.e., meeting the lower bound of diversity gain, and the optimal coding gain. In addition, a near optimal power allocation that maximizes the received SNR of the worse link is presented and examined through comprehensive computer simulations for various kinds of asymmetric relay channels.

In this paper, a novel OFDM symbol timing recovery method, which is robust to doubly selective fading channels and carrier frequency offset, is proposed for the mobile terminals of CMMB system. The time slot timing synchronization is accomplished by using the inverse sliding correlation between the segmenting Sync sequences, which possess the inverse conjugate symmetry (ICS) characteristic. Furthermore, a fast fine OFDM symbol timing algorithm based on the auto-correlation property of Sync sequences in frequency domain is also presented. According to a detection strategy for the valid taps of current channel, the specific multi-path distribution situation can be obtained. The simulation results show that compared with conventional methods, two proposed algorithm can provide a more accurate and fast estimation for symbol timing offset even in very adverse fading channels.